• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.137-157
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• 2017

As unemployment rises and economic growth slows, interest in startups, which is considered to be the driving force of job creation, is increasing. This study aimed to analyze the employment effects of knowledge-based startups in South Korea. In particular, startups were divided into three categories (knowledge-based manufacturing, knowledge-based service, and other industries) and the region were divided into the capital region and the other regions. The result of the analysis, which used census on Establishments Data from Statistics Korea(KOSIS), showed that the employment effects of startups change in three steps over time. When new firms were created, employment increases instantly. However, as the competition among firms increases, some firms exit the market and employment decreases. In the long-term, some firms will survive the market competition and increase their firm size and the number of jobs they offer. The total employment effect was greater for knowledge-based startups than the other industries startups. The total employment effect of knowledge-based startups are 2.84%p for the period of 6 years. Startups in the Capital region showed higher employment effect than startups in other regions. This implies that in the capital region, employment increases more after the startups are created, but due to fierce competition, employment also decreases relatively more than it does in other regions. However, companies that survive competition create more employment. This study may give some policy implications that startup policies should be tailored to the startup's type and regional characteristics in order to achieve more effective job creation performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.72-82
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• 2018

In this paper, we identify risk factors that are likely to occur during the lifecycle of a new product development (NPD) project from the literatures, and identify the three objectives or three constraints that will ultimately be achieved for project success in the ICT industry : performance (scope/quality), schedule (time), and cost. Firstly, we interviewed the project experts to classify the risk factors according that the final project objectives are changeable based on scope/quality, time and cost budget constraints. Secondly, the survey for pairwise comparisons between the risk factors was asked to the project managers and members who had ever actually participated in the NPD projects of ICT industry to determine the priority ranks on relative importance using AHP (Analytic Hierarchy Process). The risk factors negatively affecting the goals of projects were analyzed by using the AHP respectively in four project stages during the life cycle of the project. The comparison of risk factors within each stage is a different approach unlike the literatures which have covered project's overall risk assessment. There is an advantage that risk management can be effectively performed with priorities according to each stage from the start to the end of the project. In other words, it is necessary to identify what risk factors will occur in each stage, and to have ideas at each stage with the priorities so that they can be mitigated and eliminated before actual occurrence. As a result, risks on scope & quality changes were found to be the most important considerations for initiative stage of NPD projects in the ICT industry, whereas in the final stage, risks on schedule (time) changes were the most important priorities. Among the ICT industry product categories, 'communication and broadcasting devices' and 'IT and communication based devices' generally have a high priority in terms of risks on scope & quality changes when initiating the project. At the closing stage of the project, however, considering that schedule (time) changeable risk is getting higher, these products tend to target at B2B market rather than B2C because the new products must be delivered and launched in time as customer firm required.

• Knowledge Management Research
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• v.24 no.3
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• pp.53-71
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• 2023

Environmental, Social, and Governance (ESG) refers to factors that are important for assessing a firm's social and environmental effect, as well as its governance standards. This paper investigates the relationship between ESG-based corporate governance and SDGs strategy implementation by discussing about incorporating ESG issues into corporate operations. It digs into the advantages and disadvantages of aligning corporate governance with the SDGs, demonstrating the potential for delivering long-term value for both firms and society as a whole. In this paper, we investigate ESG-Based Knowledge Management (ESG-KM), a knowledge management system that incorporates sustainability principles. More specifically, the paper investigates how the synergy between ESG-KM and ESG-Based Corporate Governance (ESG-CG) might influence firms' long-term value creation, stakeholder involvement, and sustainable decision-making. Finally, this paper investigates how public organizations might use knowledge management to improve the implementation and effect of ESG-CG principles, resulting in better sustainable outcomes. Public enterprises may support responsible decision-making, increase stakeholder involvement, and achieve long-term performance by linking ESG principles with corporate governance standards. The paper then explores how ESG-KM might help public firms integrate these concepts into their governance structures. The scientific novelty of this paper resides in its thorough investigation, realistic implementation methodologies, and novel combination of ESG principles, corporate governance, and knowledge management. Furthermore, by providing actionable insights and emphasizing the application of these concepts in the context of public enterprises, the paper makes a valuable contribution to the field of management, propelling the discourse on responsible and sustainable business practices in both the private and public sectors.

• Journal of dental hygiene science
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• v.3 no.1
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• pp.5-10
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• 2003

The purpose of this study was to examine how medical personnels in the field of dentistry perceived the introduction of the yearly income system in an effort to determine some of the right directions for that and find out in which way that could be vitalized. For that purpose, literature concerned and relevant materials were reviewed, and a survey was conducted on 95 medical personnels, who were working at dental hospitals and clinics throughout the nation, for approximately five months from April through August 2002. After the collected data were analyzed, the following findings were acquired; (1) Regarding their awareness of the yearly income system by the type of institute, the workers from the dental hospitals found the yearly income system, more than the others from the dental clinics did, to enlarge their sense of involvement in management (p<.001), further work productivity(p<.01), awake their target-oriented sense of mission(p<.01) and make them feel uneasy about their future(p<.05). (2) As to differences between the dentists and dental hygienists, the former group had a higher opinion about that system(p<.01) and its effect on impartial performance appraisal(p<.01), encouraging medical personnels to deploy their abilities(p<.01), furthering work productivity(p<.001), intensifying a target-oriented sense of mission(p<.001). (3) Concerning their perception by career, those who had longer experience to work in that field considered it to strengthen work severity(p<.05) more than the others who had shorter experience did, and the former group thought that system was more likely to concentrate on a short-term achievement (p<.05). The workers who had been working for three to five years were more conscious of change in office hours (p<.01), and those who had been working for two or less years viewed that system most favorably(p<.05). (4) In order for that system to be successful, impartial performance appraisal was most widely called for(31.6%), followed by trust between labor and management(26.3%), worker's positive attitude toward that system(16.8%), CEO's firm belief in that(12.3%), and setting up a feasible target. The workers from the dental hospitals put more stress on medical personnel's favorable attitude toward that system(p<.05) than the others from the dental clinics did. And the dentists placed more stock in setting up a feasible target, which was a criteria of determining the amount of annual income, than the dental hygienists did.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.69-80
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• 2015

This can be promoted collaboration environment for the system and the system is very important for competitiveness, it is equipped. If so, could work in collaboration with members of the organization to promote collaboration what factors? Organizational collaboration and cooperation of many people working, or worth pursuing common goals by sharing information and processes to improve labor productivity, defined as collaboration. Factors that promote collaboration are shared visions, the organization's principles and rules that reflect the visions, on-line system developments, and communication methods. First, it embodies the vision shared by the more sympathetic members are active and voluntary participation in the activities of the organization can be achieved. Second, the members are aware of all the rules and principles of a united whole is accepted and leads to good performance. In addition, the ability to share sensitive business activities for self-development and also lead to work to make this a regular activity to create a team that can collaborate to help the environment and the atmosphere. Third, a systematic construction of the online collaboration system is made efficient and rapid task. According to Student team and A corporation we knew that Cloud services and social media, low-cost, high-efficiency services could achieve. The introduction of the latest information technology changes, the members of the organization's systems and active participation can take advantage of continuing education must be made. Fourth, the company to inform people both inside and outside of the organization to communicate actively to change the image of the company activities, the creation of corporate performance is very important to figure. Reflects the latest trend to actively use social media to communicate the effort is needed. For development of systematic collaboration promoting model steps to meet the organizational role. First, the Chief Executive Officer to make a firm and clear vision of the organization members to propagate the faith, empathy gives a sense of belonging should be able to have. Second, middle managers, CEO's vision is to systematically propagate the organizers rules and principles to establish a system would create. Third, general operatives internalize the vision of the company stating that the role of outside companies must adhere. The purpose of this study was well done in collaboration organizations promoting factors for strategic alignment model based on the golden circle and collaboration to understand and reflect the latest trends in information technology tools to take advantage of smart work and business know how student teams through case analysis will derive the success factors. This is the foundation for future empirical studies are expected to be present.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of Distribution Research
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• v.17 no.1
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• pp.65-86
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• 2012

The $20^{th}$ century was the era of manufacturer brands which built higher brand equity for consumers. Consumers moved from generic products of inconsistent quality produced by local factories in the $19^{th}$ century to branded products from global manufacturers and manufacturer brands reached consumers through distributors and retailers. Retailers were relatively small compared to their largest suppliers. However, sometime in the 1970s, things began to slowly change as retailers started to develop their own national chains and began international expansion, and consolidation of the retail industry from mom-and-pop stores to global players was well under way (Kumar and Steenkamp 2007, p.2) In South Korea, since the middle of the 1990s, the bulking up of retailers that started then has changed the balance of power between manufacturers and retailers. Retailer private labels, generally referred to as own labels, store brands, distributors own private-label, home brand or own label brand have also been performing strongly in every single local market (Bushman 1993; De Wulf et al. 2005). Private labels now account for one out of every five items sold every day in U.S. supermarkets, drug chains, and mass merchandisers (Kumar and Steenkamp 2007), and the market share in Western Europe is even larger (Euromonitor 2007). In the UK, grocery market share of private labels grew from 39% of sales in 2008 to 41% in 2010 (Marian 2010). Planet Retail (2007, p.1) recently concluded that "[PLs] are set for accelerated growth, with the majority of the world's leading grocers increasing their own label penetration." Private labels have gained wide attention both in the academic literature and popular business press and there is a glowing academic research to the perspective of manufacturers and retailers. Empirical research on private labels has mainly studies the factors explaining private labels market shares across product categories and/or retail chains (Dahr and Hoch 1997; Hoch and Banerji, 1993), factors influencing the private labels proneness of consumers (Baltas and Doyle 1998; Burton et al. 1998; Richardson et al. 1996) and factors how to react brand manufacturers towards PLs (Dunne and Narasimhan 1999; Hoch 1996; Quelch and Harding 1996; Verhoef et al. 2000). Nevertheless, empirical research on factors influencing the production in terms of a manufacturer-retailer is rather anecdotal than theory-based. The objective of this paper is to bridge the gap in these two types of research and explore the factors which influence on manufacturer's private label production based on two competing theories: S-C-P (Structure - Conduct - Performance) paradigm and resource-based theory. In order to do so, the authors used in-depth interview with marketing managers, reviewed retail press and research and presents the conceptual framework that integrates the major determinants of private labels production. From a manufacturer's perspective, supplying private labels often starts on a strategic basis. When a manufacturer engages in private labels, the manufacturer does not have to spend on advertising, retailer promotions or maintain a dedicated sales force. Moreover, if a manufacturer has weak marketing capabilities, the manufacturer can make use of retailer's marketing capability to produce private labels and lessen its marketing cost and increases its profit margin. Figure 1. is the theoretical framework based on a strategic market management perspective, integrated concept of both S-C-P paradigm and resource-based theory. The model includes one mediate variable, marketing capabilities, and the other moderate variable, competitive intensity. Manufacturer's national brand reputation, firm's marketing investment, and product portfolio, which are hypothesized to positively affected manufacturer's marketing capabilities. Then, marketing capabilities has negatively effected on private label production. Moderating effects of competitive intensity are hypothesized on the relationship between marketing capabilities and private label production. To verify the proposed research model and hypotheses, data were collected from 192 manufacturers (212 responses) who are producing private labels in South Korea. Cronbach's alpha test, explanatory / comfirmatory factor analysis, and correlation analysis were employed to validate hypotheses. The following results were drawing using structural equation modeling and all hypotheses are supported. Findings indicate that manufacturer's private label production is strongly related to its marketing capabilities. Consumer marketing capabilities, in turn, is directly connected with the 3 strategic factors (e.g., marketing investment, manufacturer's national brand reputation, and product portfolio). It is moderated by competitive intensity between marketing capabilities and private label production. In conclusion, this research may be the first study to investigate the reasons manufacturers engage in private labels based on two competing theoretic views, S-C-P paradigm and resource-based theory. The private label phenomenon has received growing attention by marketing scholars. In many industries, private labels represent formidable competition to manufacturer brands and manufacturers have a dilemma with selling to as well as competing with their retailers. The current study suggests key factors when manufacturers consider engaging in private label production.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Magazine of the Korean Society of Agricultural Engineers
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• v.13 no.1
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• pp.2206-2217
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• 1971

Spillway and discharge channel of reservoirs require the Control of Large volume of water under high pressure. The energies at the downstream end of spillway or discharge channel are tremendous. Therefore, Some means of expending the energy of the high-velocity flow is required to prevent scour of the riverbed, minimize erosion, and prevent undermining structures or dam it self. This may be accomplished by Constructing an energy dissipator at the downstream end of spillway or discharge channel disigned to dissipated the excessive energy and establish safe flow Condition in the outlet channel. There are many types of energy dissipators, stilling basins are the most familar energy dissipator. In the stilling basin, most energies are dissipated by hydraulic jump. stilling basins have some length to cover hydraulic jump length. So stilling basins require much concrete works and high construction cost. Flip bucket type energy dissipators require less construction cost. If the streambed is composed of firm rock and it is certain that the scour will not progress upstream to the extent that the safety of the structure might be endangered, flip backet type energy dissipators are the most recommendable one. Following items are tested and studied with bucket radius, $R=7h_2$,(medium of $4h_2{\geqq}R{\geqq}10h_2$). 1. Allowable upstream channel slop of bucket. 2. Adequate bucket lip angle for good performance of flip bucket. Also followings are reviwed. 1. Scour by jet flow. 2. Negative pressure distribution and air movement below nappe flow. From the test and study, following results were obtained. 1. Upstream channel slope of bucket (S=H/L) should be 0.25<H/L<0.75 for good performance of flip bucket. 2. Adequated lip angle $30^{\circ}{\sim}40^{\circ}$ are more reliable than $20^{\circ}{\sim}30^{\circ}$ for the safety of structures.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.